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Development of CD3 cell quantitation algorithms for renal allograft biopsy rejection assessment utilizing open source image analysis software

Authors
  • Moon, Andres1
  • Smith, Geoffrey H.1
  • Kong, Jun2
  • Rogers, Thomas E.1
  • Ellis, Carla L.1
  • Farris, Alton B. “Brad” III1, 3
  • 1 Emory University, Department of Pathology, Atlanta, GA, USA , Atlanta (United States)
  • 2 Emory University, Department of Bioinformatics, Atlanta, GA, USA , Atlanta (United States)
  • 3 Emory University Hospital, 1364 Clifton Road NE, Room H-188, Atlanta, GA, 30322, USA , Atlanta (United States)
Type
Published Article
Journal
Virchows Archiv
Publisher
Springer Berlin Heidelberg
Publication Date
Nov 08, 2017
Volume
472
Issue
2
Pages
259–269
Identifiers
DOI: 10.1007/s00428-017-2260-6
Source
Springer Nature
Keywords
License
Yellow

Abstract

Renal allograft rejection diagnosis depends on assessment of parameters such as interstitial inflammation; however, studies have shown interobserver variability regarding interstitial inflammation assessment. Since automated image analysis quantitation can be reproducible, we devised customized analysis methods for CD3+ T-cell staining density as a measure of rejection severity and compared them with established commercial methods along with visual assessment. Renal biopsy CD3 immunohistochemistry slides (n = 45), including renal allografts with various degrees of acute cellular rejection (ACR) were scanned for whole slide images (WSIs). Inflammation was quantitated in the WSIs using pathologist visual assessment, commercial algorithms (Aperio nuclear algorithm for CD3+ cells/mm2 and Aperio positive pixel count algorithm), and customized open source algorithms developed in ImageJ with thresholding/positive pixel counting (custom CD3+%) and identification of pixels fulfilling “maxima” criteria for CD3 expression (custom CD3+ cells/mm2). Based on visual inspections of “markup” images, CD3 quantitation algorithms produced adequate accuracy. Additionally, CD3 quantitation algorithms correlated between each other and also with visual assessment in a statistically significant manner (r = 0.44 to 0.94, p = 0.003 to < 0.0001). Methods for assessing inflammation suggested a progression through the tubulointerstitial ACR grades, with statistically different results in borderline versus other ACR types, in all but the custom methods. Assessment of CD3-stained slides using various open source image analysis algorithms presents salient correlations with established methods of CD3 quantitation. These analysis techniques are promising and highly customizable, providing a form of on-slide “flow cytometry” that can facilitate additional diagnostic accuracy in tissue-based assessments.

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